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| # ORA Training Environment | |
| This directory contains the scripts and configuration for Fine-Tuning a custom LLM (e.g., Llama 3) for the ORA Spiritual Assistant. | |
| ## Prerequisites | |
| - Python 3.10+ | |
| - CUDA-capable GPU (NVIDIA) or Mac with M-series chip | |
| - Ollama (for local testing) | |
| ## Setup | |
| 1. Create a virtual environment: | |
| ```bash | |
| python -m venv venv | |
| source venv/bin/activate # or venv\Scripts\activate on Windows | |
| ``` | |
| 2. Install dependencies: | |
| ```bash | |
| pip install -r requirements.txt | |
| ``` | |
| ## Workflow | |
| 1. **Prepare Data**: Place your data (JSONL format) in `data/`. | |
| 2. **Fine-Tune**: Run the training script (coming soon). | |
| 3. **Export**: Convert LoRA adapters to GGUF format. | |
| 4. **Serve**: Load into Ollama. | |